Emergence of a multiple-input multiple-output (Multiple-Input Multiple-Output, MIMO) technology has brought dramatically changes to wireless communications. A plurality of antennas are deployed on a transmit end device and a receive end device, so that the MIMO technology can significantly improve performance of a wireless communications system. For example, in a diversity scenario, the MIMO technology can effectively improve transmission reliability, and in a multiplexing scenario, the MIMO technology can greatly improve a transmission throughput.
In a MIMO system, a precoding technology is usually used to improve a channel, to enhance a spatial multiplexing (Spatial Multiplexing) effect. Specifically, the precoding technology uses a precoding matrix matching the channel to process a data stream of spatial multiplexing (briefly referred to as a spatial stream below), so as to precode the channel and improve receiving quality of the spatial stream.
The precoding matrix usually includes a plurality of column vectors. Each column vector may also be referred to as a precoding vector, and each precoding vector is used to precode a spatial stream. An ideal precoding vector used for describing a channel matrix may be obtained by performing singular value decomposition (Singular Value Decomposition, SVD) on the channel matrix. If the ideal precoding vector is directly fed back, feedback overheads are very high. In the prior art, a precoding vector is determined based on a codebook, a column vector is selected from the codebook as the precoding vector directly, and an identifier of the selected column vector is used for feedback. However, because a codebook space is limited, the precoding vector selected based on the codebook deviates greatly from the ideal precoding vector, resulting in a limited precoding effect. It can be learned that a new feedback mechanism is required to improve the precoding effect.